Orientation-Dependent Window Area: Linking Solar Gains and Transmission Losses to Annual Heating and Cooling Loads

Abstract

Energy efficiency in hospitals—where continuous operation with high internal gains and strict comfort needs—demands facade strategies tailored to climate. This study quantifies how the window-to-wall ratio (WWR) distribution and city-specific envelope properties affect the annual heating and cooling loads of a four-story, 3000 m² hospital in Turkey. Energy simulations were conducted using DesignBuilder (2021) with EnergyPlus under a controlled modeling framework, following ASHRAE healthcare guidelines for internal loads and TS 825:2024 for envelope compliance. Three locations were selected to span national variability: Bursa (Marmara—temperate/transition), Mersin (Mediterranean—hot–humid), and Kars (humid continental—cold). Scenario 1 (S1) assigned a graduated WWR on the south facade by floor—20%, 30%, 40%, and 50% from ground to top—while the north, east, and west facades were held at 20%, 30%, and 20%. Scenario 2 (S2) preserved the same geometry and WWR values but applied the graduated WWR to the north facade instead, keeping the south at 20%, east at 30%, and west at 20%. Within each city, opaque and glazing properties were kept constant across scenarios to isolate WWR–orientation effects. For every city–scenario combination, annual space-heating and space-cooling loads were computed, and window heat gains and losses were analyzed on the facade with variable WWR to support interpretation of performance mechanisms. The results indicate that S2 outperforms S1 in Mersin, S1 outperforms S2 in Kars, and S2 offers a moderate advantage in Bursa.

1. Introduction

Buildings’ energy consumption is becoming an increasingly important issue in Turkey, as it is worldwide. Rising population, growing energy demand, and limited natural resources necessitate the adoption of energy-efficient design strategies. The building envelope stands out as one of the most critical components governing heat losses and gains.

In this context, glazing properties have frequently been investigated in relation to thermal and visual comfort in buildings [1]. Similarly, the window-to-wall ratio (WWR) has been shown to have a significant effect on building energy consumption and performance under various conditions [2]. A recent large-scale parametric study using EnergyPlus investigated glazing type, WWR, and orientation across extensive model runs and showed that their combined effects vary nonlinearly with climate, highlighting the need for context-sensitive optimization of window design [3]. In hot semi-arid climates, combined effects of glazing, orientation, and WWR on heating and cooling demand have also been demonstrated, further underscoring climatic sensitivity [4].

Across climates, the WWR–orientation–climate interaction has been repeatedly demonstrated to influence energy loads; optimal WWR commonly clustered around 30–45%, while south-facade optima were observed to shift due to solar-gain control [1,3,4,5]. In Mediterranean and Mediterranean-adjacent warm climates, prioritizing external shading and lower-g glazing on south facades was reported to suppress cooling loads [6]. These findings collectively indicate that envelope decisions—particularly WWR and glazing selection—should be treated as climate- and orientation-dependent design variables rather than fixed rules of thumb.

Recent simulation-based studies in healthcare settings further emphasize the importance of facade design on both energy and daylight performance under operational constraints. One Intensive Care Unit (ICU) focused study showed that WWR, window position, and surface reflectance substantially affect daylight autonomy and circadian stimulus metrics in Mediterranean contexts (Barcelona and Seville), with energy and comfort implications across facade orientations [7]. Another patient-room study incorporated energy simulation, daylight analysis, and life cycle assessment (LCA), concluding that glazing type, orientation, and wall reflectance jointly impact environmental and occupant-centered performance metrics [8]. In healthcare applications, decision-grade simulation studies commonly recommend calibration (where data are available) and basic sensitivity checks to improve the reliability of envelope-related conclusions [9,10]. In inpatient rooms, ventilation strategies (heat recovery, pressure regime, air distribution) have been identified as safety-critical, in addition to their energy impact, indicating that facade decisions should be considered together with HVAC [11].

Hospital buildings differ from other types because they operate 24/7, host high internal loads, and encompass complex spatial functions. Accordingly, energy simulation and facade design studies for healthcare facilities warrant special attention. Calibrated modeling work has evaluated how well simulated hospital energy use aligns with metered consumption and demonstrates the value of calibration for decision-grade analysis [12]. A methodological contribution further addresses model calibration under data scarcity and complexity in healthcare settings, providing practical steps for reliable performance assessment [13]. In hot, arid climates, a simulation study on hospital wards demonstrated that optimizing WWR, glazing properties, and orientation can significantly reduce cooling loads, particularly when local weather data is integrated into the design process [14].

Facade configuration and envelope properties perform differently across climates; climate-responsive design is therefore essential. Optimization studies conducted across multiple climates show that varying WWR influences building energy performance in orientation- and climate-dependent ways [15]. Earlier work likewise explored optimum glazing-to-wall ratios across several climates, focusing on minimizing heating/cooling loads and orientation effects. In a case study across Saudi Arabia’s hot–dry, hot–humid, and moderate regions, south and east facades showed the highest heat gains, with recommended WWRs of approximately 10% for hot–dry/hot–humid climates and approximately 20% for moderate climates [16].

Within the Turkish context, a numerical study quantified how glazing area, type, and orientation shape energy use and thermal loads through detailed simulations on typical summer and winter design days [17]. In addition, Turkish simulation and empirical studies confirm that WWR and envelope decisions remain climate-sensitive across regions. A 100 m² dwelling was modeled in DesignBuilder (2021; EnergyPlus engine) under two scenarios with changing WWR and was evaluated across different climatic conditions and pilot provinces, reinforcing the sensitivity of envelope design to both facade glazing and regional climate [18]. Similarly, a study conducted in Elazığ examined the combined effects of WWR and wall-material thermal properties, underscoring the role of material selection in shaping energy performance [19]. Additional national research has emphasized that Turkey is experiencing increased climatic variability—including extremes in temperature and precipitation—which strengthens the case for adaptive envelope strategies [20]. In cold-climate hospital contexts, empirical analyses of energy use identify efficiency potentials that inform facade and material decisions [21].

In this study, the annual energy performance of a four-story hospital building is analyzed for three Turkish cities representing different climate zones (Bursa, Mersin, and Kars). The analysis is based on controlled energy simulations conducted using DesignBuilder (EnergyPlus), with consideration given to floor-dependent window-to-wall ratios (WWR) applied to the building facades. Two WWR configurations are compared for the same hospital building—where geometry, function, and material properties are kept constant within each city—to evaluate the effect of WWR variation on annual energy loads across the three representative locations. Additionally, facade-level window heat gains and losses are assessed to better understand the underlying mechanisms driving whole-building energy demand.

2. Method

In this study, energy simulations were conducted using the EnergyPlus (Version 9.4.0) (U.S. Department of Energy, Washington, DC, USA) implemented throughthe DesignBuilder interface (v6.1.8.021, DesignBuilder Software Ltd., Stroud, UK) [22]. A four-story hospital building with a total indoor area of 3000 m² was defined for the simulations, with each floor having an area of 750 m². Floor levels were defined as the ground, first, second, and third floors.

With the TS 825:2024 revision, Turkey’s thermal insulation standard was updated to define six climate zones and to explicitly address cooling in addition to heating. Accordingly, Bursa (provincial center; Zone 3, Marmara—temperate/transition), Mersin (provincial center; Zone 1, Mediterranean—hot–humid), and Kars (adopting the province’s colder Zone 6 regime rather than the provincial center; humid continental—cold) were selected as representative locations [23]. For each city, the hospital building’s annual energy use was computed, with heating and cooling loads reported explicitly. To isolate orientation-dependent effects, window heat gains and losses were analyzed and reported for the facade with variable WWR under controlled conditions.

Two scenarios were developed to isolate orientation-dependent WWR effects under city-specific envelope properties. In Scenario 1, the south facade WWR increases by floor (20%, 30%, 40%, and 50% from the ground to the third floor), while the other facades remain constant (north 20%, east 30%, and west 20%). In Scenario 2, the same by-floor WWR increase is applied to the north facade (20%, 30%, 40%, and 50% from the ground to the third floor), keeping the south at 20% and the east and west facades unchanged (30% and 20%, respectively).

Table 1. Window-to-wall ratios (WWR) for scenarios (S1 and S2) by facade orientation and floor level.

Scenarios	WWR *1
S1	North = 20%, East = 30%, West = 20% South = 20%/30%/40%/50% (by floor *2)
S2	South = 20%, East = 30%, West = 20% North = 20%/30%/40%/50% (by floor *2)

*¹ WWR (window-to-wall ratio) is defined as the ratio of window area to exterior wall area. *² “By floor” indicates that the WWR is 20% at the ground floor, 30% at the first floor, 40% at the second floor, and 50% at the third floor.

summarizes the WWR definitions for Scenarios S1 and S2 by facade and floor level, while Figure 1 schematically illustrates the two configurations, emphasizing the floor-dependent WWR distribution on the variable facade.

The floor-dependent increase in window-to-wall ratio (WWR) was defined to reflect common spatial arrangements observed in hospital buildings. In typical hospital layouts, upper floors often accommodate patient rooms and spaces with higher daylight requirements, where larger window areas are preferred, while lower floors predominantly contain technical and clinical spaces with reduced reliance on natural lighting. Accordingly, the selected WWR distributions were designed to reflect a realistic but simplified floor-based functional arrangement, rather than an arbitrary geometric variation.

Within this framework, the simulation setup represents a targeted approach that isolates WWR and orientation effects while holding all other design variables constant within each city. All scenarios adhere to ASHRAE 90.1-2021 [24]. Within each city, opaque envelope and glazing properties were kept constant, and only the orientation-wise distribution of WWR differed between Scenario 1 and Scenario 2. Accordingly, comparisons were conducted between scenarios within the same location (e.g., Bursa–S1 vs. Bursa–S2; Mersin–S1 vs. Mersin–S2; Kars–S1 vs. Kars–S2).

• The opaque envelope and glazing properties were defined in accordance with TS 825:2024. Opaque assemblies complied with city-specific U-value limits, and glazing was selected to satisfy region-specific solar heat gain (g-value) requirements [23].
• The building was modeled with a flat roof slab exposed to outdoor conditions; therefore, the ceiling of the top floor was treated as the roof assembly. For each city, roof construction complied with the local TS 825:2024 U-value requirement and was kept constant across scenarios.
• Lighting was excluded as an electrical end-use. Its thermal impact was represented as internal gains using a lighting-equivalent power density with specified radiant and convective fractions, so that the reported heating and cooling loads include the effect of lighting-induced heat gains.
• Domestic hot water (DHW) demand was not modeled and is outside the scope of the present analysis.
• A generic hospital ward profile (patient rooms and associated areas) was adopted as the representative space type to ensure consistent, scenario-driven comparisons across climates.
• Healthcare-specific internal gains, occupancy assumptions, and operational practices followed ASHRAE Handbook—HVAC Applications (Healthcare) [25].
• Ventilation inputs referenced ASHRAE/ASHE Standard 170-2021 [26].
• Infiltration was set to a constant 0.20 ACH (h⁻¹) with wind and stack effects disabled to avoid double-counting with mechanical ventilation and to isolate facade/WWR impacts.
• Indoor comfort conditions followed the UK National Calculation Methodology (NCM) framework and were adapted to TS 825 temperature thresholds [23,27].
• External climate data were obtained from the IWEC2 (2021) dataset, which provides hourly climatic information, including dry-bulb temperature, solar radiation, and relative humidity [28]. Wind speed was used only to compute exterior convective heat-transfer coefficients, not for wind-driven infiltration or structural loading.

Accordingly, facade-level window heat gains and losses were reported only for the facade with variable WWR.

2.1. Operational Assumptions and Internal Loads

For both scenarios, the shared model inputs are provided in

Table 2. Internal loads and comfort assumptions used in the energy simulation model for the generic hospital ward.

Item	Description
Space/Activity type	Hospital–Inpatient ward/Patient room (generic)
Occupancy density	0.08 persons/m2 (≈12.5 m2 per person; patient + attendant average)
Metabolic rate (met)	1.1 met (sitting/standing, light activity)
Clothing (clo)	Winter: 1.0 clo; Summer: 0.5 clo
Lighting target (lux)	300 lux (typical for patient rooms/general areas)
Lighting internal gains	8 W/m2 (patient rooms; schedule: 06:00–22:00 = 1.0; 22:00–06:00 = 0.3)
Equipment internal gains	12 W/m2 (medical/office equipment mix, conservative)
People sensible/latent	Sensible ~70 W/person, Latent ~45 W/person (typical for 1.1 met)

(common occupancy and indoor environmental parameters) and

Table 3. HVAC and operational assumptions used in the energy simulations for the generic hospital ward.

Item	Description
HVAC template	Central AHU + terminal units (generic ward); code-compliant, no optimization; availability schedule: 24/7 in wards
Mechanical ventilation	On (24/7 availability)
Thermostat setpoints	Heating 21 °C (setback 19 °C); Cooling 24 °C (setup 26 °C)
Heating/Cooling supply air temperature	32 °C/12 °C
Heating source/ Seasonal efficiency	Natural gas (hot-water boiler), η_seasonal ≈ 0.90
Cooling system/Seasonal COP	≈3.2 (air-cooled chiller, conservative)
Operation (heating/cooling)	24/7 ward schedule (diurnal variation)
Humidity control	Not actively controlled (temperature control only)
Natural ventilation	On—by zone (non-critical areas only)
Outdoor air (ventilation)	Outdoor air ≥2 ACH, Total supply 6 ACH (24/7; typical per ASHRAE 170; neutral pressure, generic ward)
Infiltration	Fixed 0.20 h−1 (ACH); wind-driven infiltration and structural wind loads are outside the scope

(system and operational parameters), unless noted otherwise.

The HVAC and operational assumptions summarized in Table 3 were intentionally defined at a load-calculation level representative of typical hospital operation. The objective was to enable consistent comparison of annual heating and cooling demands across facade orientation and WWR scenarios, rather than to model detailed HVAC system design or control strategies. Accordingly, a generic, continuously operating system configuration was adopted to reflect hospital ward conditions while maintaining comparability between scenarios.

2.2. Dimensions and Properties of Selected Material

In accordance with TS 825:2024, the prescriptive envelope performance limits (U-values and solar heat gain coefficient, SHGC) for the selected locations are summarized in

Table 4. TS 825:2024 prescriptive U-value limits (reference) and window performance limits (U-value and SHGC), with selected glazing g-values [23].

City	Climate Zone	U_Wall *1	U_Roof *1	U_Ground *1	Code Limit U_Window *2	Modeled U_Window *2	SHGC *3	Selected g (Glazing Model) *4
Bursa	3	0.40	0.30	0.35	1.8	1.5	≤0.45	0.40
Mersin	1	0.45	0.35	0.40	1.8	1.5	≤0.45	0.40
Kars	6	0.25	0.20	0.25	1.8	1.5	≥0.55	0.60

Units: W/(m²·K), SHGC is dimensionless. *¹ U_Wall, U_Roof, and U_Ground are TS 825:2024 prescriptive maximum U-value limits (reference values; not simulation inputs); U-values denote overall (assembly) thermal transmittance of envelope elements (indoor-to-outdoor/ground), not individual layer properties. *² TS 825:2024 prescriptive window U-value limit is U_Window ≤ 1.8 W/(m²·K); the modeled whole-window U-value is U_Window ≈ 1.5 W/(m²·K) for all locations. *³ TS 825:2024 climate-specific SHGC (g-value) limits are shown as reference values. *⁴ Selected glazing g-values used in the simulations, chosen to comply with TS 825:2024 SHGC limits.

for reference [23]. These values represent code limits rather than the exact simulation inputs. The actual envelope constructions used in the simulations were defined through layered assemblies and are reported in

Table 5. Building envelope materials and layered constructions for Bursa (common to S1–S2) [22,23].

Bursa, Turkey (Zone 3, Marmara—Temperate/Transition)
External Wall Layers	Ground-Floor Layers	Rooftop Layers
(exterior → interior) U_wall = 0.39 W/(m2·K)	(soil side → room) U_ground = 0.32 W/(m2·K)	(outdoor side → room) U_roof *2 = 0.29 W/(m2·K)
Mineral render (exterior finish) 0.015 m *1 Air barrier/WRB (water-resistive barrier) 0.0015 m Graphite EPS insulation (λ ≈ 0.031) 0.055 m Hollow clay block (HCB) infill 0.190 m Gypsum plasterboard 0.012 m	Reinforced concrete slab 0.120 m PE/EPDM moisture barrier 0.001 m XPS 0.100 m Cement–sand screed 0.050 m Floor finish (vinyl/linoleum) 0.003 m	Waterproofing membrane 0.004 m XPS 0.110 m Vapor retarder 0.0003 m Reinforced concrete slab 0.140 m Gypsum plasterboard 0.012 m

*¹ Thicknesses are given in meters (m). *² U_roof refers to the flat roof (top-floor slab) assembly represented by the “Rooftop layers” listed from the outdoor side to the room side.

,

Table 6. Building envelope materials and layered constructions for Mersin (common to S1–S2) [22,23].

Mersin, Turkey (Zone 1, Mediterranean—Hot–Humid)
External Wall Layers	Ground-Floor Layers	Rooftop Layers
(exterior → interior) U_wall = 0.36 W/(m2·K)	(soil side → room) U_ground = 0.39 W/(m2·K)	(outdoor side → room) U_roof *2 = 0.33 W/(m2·K)
Mineral render (exterior finish) 0.012 m *1 Air barrier/WRB (water-resistive barrier) 0.0015 m Graphite EPS insulation (λ ≈ 0.031) 0.030 m Autoclaved aerated concrete 0.200 m Gypsum plasterboard 0.012 m	Reinforced concrete slab 0.120 m PE/EPDM moisture barrier 0.001 m XPS 0.080 m Cement–sand screed 0.050 m Floor finish (vinyl/linoleum) 0.003 m	Reflective roofing membrane 0.003 m EPS insulation 0.100 m Vapor retarder 0.0003 m Reinforced concrete slab 0.120 m Gypsum plasterboard 0.011 m

*¹ Thicknesses are given in meters (m). *² U_roof refers to the flat roof (top-floor slab) assembly represented by the “Rooftop layers” listed from the outdoor side to the room side.

and

Table 7. Building envelope materials and layered constructions for Kars (common to S1–S2) [22,23].

Kars, Turkey (Zone 6, Humid Continental—Cold)
External Wall Layers	Ground-Floor Layers	Rooftop Layers
(exterior → interior) U_wall = 0.24 W/(m2·K)	(soil side → room) U_ground = 0.25 W/(m2·K)	(outdoor side → room) U_roof *2 = 0.19 W/(m2·K)
Mineral render (exterior finish) 0.015 m *1 Mineral wool insulation (external) 0.080 m Hollow clay block (HCB) infill 0.190 m Service cavity (mineral wool infill) 0.040 m Vapor retarder 0.0003 m Gypsum plasterboard (double) 0.025 m	Reinforced concrete slab 0.150 m PE/EPDM moisture barrier 0.001 m XPS 0.090 m Cement–sand screed 0.050 m Floor finish (vinyl/linoleum) 0.003 m	Roofing membrane 0.003 m Mineral wool insulation 0.180 m Vapor retarder 0.0003 m Reinforced concrete slab 0.140 m Gypsum plasterboard 0.012 m

*¹ Thicknesses are given in meters (m). *² U_roof refers to the flat roof (top-floor slab) assembly represented by the “Rooftop layers” listed from the outdoor side to the room side.

[22], while glazing g-values were selected in compliance with the climate-specific SHGC limits given in Table 4.

In the Kars (Zone 6) case, a high-g glazing (g = 0.60) was selected in accordance with TS 825:2024, which prescribes g ≥ 0.55 in cold climates unless specific cooling-driven design constraints apply [23]. Given the 24/7 operation of the hospital, both heating and cooling demands were considered.

A single window assembly was used uniformly across all locations to isolate WWR effects: double glazing (6–16–6), low-E, argon fill, warm-edge spacer, and a multi-chamber uPVC frame (70–82 mm, dual EPDM gaskets; whole-window (glass + frame) specification). The whole-window U was ≈ 1.5 W/(m²·K) in all cases, while g was adjusted per climate to satisfy TS 825:2024 limits [23]. The use of a single, code-compliant double-glazed assembly across locations was chosen to isolate WWR effects. Comfort and condensation considerations were taken into account when selecting the glazing assembly and indoor setpoints; the adopted specifications are consistent with typical hospital envelope practice and relevant guidance [25], and no critical comfort or condensation risks were anticipated under the modeled scenarios. Windows were kept to a uniform module size—1.20 m (W) × 1.50 m (H)—and aligned to consistent sill (0.90 m) and head (2.40 m) heights on all facades. A planning grid of 1.20 m was used to coordinate facade modules and mullion spacing; scenario-specific WWR values were achieved by varying the number/spacing of modules and/or the spandrel height, not the window dimensions.

Door specification for the selected scenarios was as follows: an opaque, insulated exterior door with a powder-coated steel leaf and polyurethane foam core with a thickness of about 50 mm, set in a thermally broken aluminum frame with continuous compression gaskets and a flush, thermally broken threshold; leaf size 1.00 m (W) × 2.20 m (H) (clear opening ≥0.90 m), head height 2.40 m. The same door assembly was used uniformly across all locations and scenarios (no glazing). The overall door U-value used in the model was approximately 1.2 W/(m²·K), consistent with TS 825:2024 prescriptive limits for opaque envelope elements. Curtains/blinds and exterior shading devices were not modeled.

The opaque-envelope material layers used in the simulations are summarized in Table 5, Table 6 and Table 7. In both Scenario 1 and Scenario 2, the materials are identical within each city. Opaque-envelope U-values were specified to comply with the TS 825:2024 prescriptive maximum limits for each climate zone [23] and modeled in DesignBuilder/EnergyPlus as layered constructions; ground heat transfer was modeled using the EnergyPlus approach as implemented in DesignBuilder [22]. Table 5 corresponds to Bursa (S1–S2), Table 6 to Mersin (S1–S2), and Table 7 to Kars (S1–S2).

3. Results

After all inputs and constraints were finalized, simulations were performed in DesignBuilder (2021) using EnergyPlus.

Table 8. Window solar gains, transmission losses, and net window heat gain for the facade with varying WWR, per gross floor area kWh/(m²·yr).

City (District)	Scenario	WWR Pattern (N/E/S/W)	Window Solar Gains	Transmission Losses (U-Value)	Net Window Heat Gain
Bursa	S1	N20/E30/S20, 30, 40, 50/W20	12.67	2.66	10.01
Bursa	S2	N20, 30, 40, 50/E30/S20/W20	6.32	2.62	3.70
Mersin	S1	N20/E30/S20, 30, 40, 50/W20	15.38	2.25	13.13
Mersin	S2	N20, 30, 40, 50/E30/S20/W20	5.79	2.19	3.60
Kars	S1	N20/E30/S20, 30, 40, 50/W20	20.69	5.25	15.44
Kars	S2	N20, 30, 40, 50/E30/S20/W20	5.94	4.88	1.06

Notes. Scenario 1 (south facade WWR increases by floor) and Scenario 2 (north facade WWR increases by floor); values are normalized by gross floor area; building-wide totals (kWh/yr) are reported in Supplementary Table S1.

reports window solar gains, transmission (U-value) losses, and the resulting net window heat gain for the facade where WWR increases by floor, expressed per gross floor area kWh/(m²·yr). Complementarily,

Table 9. Annual space-heating, space-cooling, and total space-conditioning loads for the hospital model in Bursa, Mersin, and Kars under scenarios S1 and S2 (kWh/(m²·yr)).

City	Scenario	Heating	Cooling	Total
Bursa	S1	19	54	73
Bursa	S2	23	46	69
Mersin	S1	5	95	100
Mersin	S2	7	85	92
Kars	S1	81	22	103
Kars	S2	91	18	109

Notes. Values are normalized by gross floor area; building-wide totals are provided in Supplementary Table S2.

presents the annual space-heating, space-cooling, and total space-conditioning loads for the hospital model—again normalized by gross floor area rather than building totals—across Bursa, Mersin, and Kars under the same S1–S2 configurations. Together, Table 8 and Table 9 link facade-level mechanisms to whole-building energy demand. The Supplementary Material reports the building-wide annual totals (kWh/yr): Supplementary Table S1 provides the building-wide counterpart of Table 8, reporting annual window solar gains, transmission losses (U-value), and net window heat gain, while Supplementary Table S2 provides the building-wide counterpart of Table 9, reporting annual space-conditioning energy demand (heating, cooling, and total).

Findings by city, per gross floor area in kWh/(m²·yr):

• Bursa (Zone 3, Marmara—temperate/transition): On the varying facade, net window heat is higher in S1 (10.01 vs. 3.70 kWh/(m²·yr)), consistent with the heating–cooling trade-off. Solar gains decrease significantly (12.67 in S1 to 6.32 in S2), with minimal change in transmission losses (2.66 in S1 to 2.62 in S2), all in kWh/(m²·yr) (Table 8; Figure 2). Totals are close in S1 and S2 (73 vs. 69 kWh/(m²·yr); 6% difference; Table 9; Figure 3). S2 reduces cooling by 15% (from 54 to 46) but increases heating by 21% (from 19 to 23), both in kWh/(m²·yr). These countervailing changes yield a moderate reduction in the annual total (Table 9).
• Mersin (Zone 1, Mediterranean—hot–humid): Moving from S1 to S2 reduces the annual total by 8% (from 100 to 92 kWh/(m²·yr); Table 9; Figure 3). Cooling decreases by 11% (from 95 to 85), while heating increases (from 5 to 7), both in kWh/(m²·yr), remaining a small fraction of the total. On the facade where WWR increases by floor, the net window heat declines from 13.13 to 3.60 in S2. This 73% drop is mainly due to reduced solar gains (15.38 in S1 to 5.79 in S2), with minimal change in transmission losses (2.25 in S1 to 2.19 in S2), all in kWh/(m²·yr) (Table 8; Figure 2).
• Kars (Zone 6; humid continental—cold): Choosing S1 instead of S2 reduces the annual total by 6% (from 109 to 103 kWh/(m²·yr); Table 9; Figure 3). Heating decreases by 11% (from 91 to 81), whereas cooling rises (from 18 to 22), all in kWh/(m²·yr), yet cooling remains secondary in magnitude. On the varying facade, net window heat is higher in S1 (15.44 vs. 1.06 kWh/(m²·yr)), reflecting window solar gains (20.69 in S1 to 5.94 in S2) that outweigh transmission losses, (5.25 in S1 to 4.88 in S2), all in kWh/(m²·yr) (Table 8; Figure 2).

Patterns consistent across cities and scenarios (WWR/orientation effects):

• The direction of the effect is consistent with the climate. For Mersin (Zone 1, Mediterranean, hot–humid), S2 (north facade with WWR increasing by floor) is more favorable; for Kars (Zone 6, humid continental, cold), S1 (south facade with WWR increasing by floor) is advantageous; for Bursa (Zone 3, temperate/transition, Marmara), annual totals are close (Table 9).
• The mechanism is explained by solar gains, while transmission (U-value) losses play a limited role. On the varying-WWR facade, transmission losses change only slightly between S1 and S2: from 2.66 to 2.62 kWh/(m²·yr) in Bursa, 2.25 to 2.19 in Mersin, and 5.25 to 4.88 in Kars. By contrast, solar gains decrease much more: from 12.67 to 6.32 in Bursa, 15.38 to 5.79 in Mersin, and 20.69 to 5.94 in Kars, all in kWh/(m²·yr). Thus, net window heat is governed mainly by solar-gain changes across all scenarios (Table 8).
• A uniform window assembly strengthens interpretation. Keeping the same window system in all scenarios isolates WWR and orientation effects from envelope variability and improves comparability across scenarios (Table 8).
• The hospital typology keeps effects moderate at the building scale. With 24/7 operation, internal gains and continuous ventilation, facade-driven differences are clear in the window metrics but still translate to modest changes in annual totals; the changes remain in the single-digit percentage range (Bursa 6%; Mersin 8%; Kars 6%) (Table 9).
• In hot–humid contexts, south facades with higher exposure were reported to benefit from external shading and lower-g glazing to suppress cooling loads; in cold contexts with south-weighted WWR, triple glazing (low-U) with moderate-to-high g can be tested to leverage passive solar gains [6,8].
• Decisions were recommended to be co-optimized with daylight and comfort targets; in inpatient rooms, ventilation strategies (heat recovery, pressure regime, air distribution) were identified as safety-critical as well as energy-relevant, calling for integrated facade–HVAC design [11].
• For decision-grade use, calibration against metered hospital energy data and sensitivity checks were recommended, in line with established guidance [9,10].

4. Discussion

This study examines how floor-dependent window-to-wall ratio (WWR) distributions and facade orientation influence annual space-conditioning demand and facade-level heat flows in hospital buildings across contrasting climatic contexts. The analysis was based on a controlled simulation framework in which only WWR distribution and orientation were varied, while all other design parameters were held constant. Results are discussed as annual metrics normalized by gross floor area to enable consistent comparisons across climates and scenarios.

The findings indicate that orientation-sensitive WWR should be tuned to climate. In hot–humid conditions (Mersin), increasing the north-side WWR (S2) on the varying facade reduces annual energy use by limiting window solar gains. In cold conditions (Kars), increasing the south-side WWR (S1) lowers total demand by enhancing beneficial window solar gains during the heating season. In temperate/transition conditions (Bursa), S2 also performs better than S1. Across all three climates, however, the resulting differences in annual energy demand remain moderate, reflecting the dominant influence of internal gains, ventilation requirements, and near-continuous HVAC operation typical of hospital buildings. Under these conditions, local daylight availability, comfort considerations, and energy pricing may play a more prominent role in guiding design decisions. As a practical takeaway, the results suggest that designers may retain a single, efficient window assembly and adjust WWR primarily by orientation. In hot–humid climates, configurations similar to S2 are likely to be more favorable, while in cold climates, configurations resembling S1 appear advantageous when combined with improved thermal performance. These observations should be interpreted as orientation-sensitive tendencies rather than prescriptive design rules.

Consistent with prior literature on climate-responsive facades, this study isolated WWR and orientation effects by holding the window system constant across all cases. The observed pattern—higher north-side WWR performing better in hot–humid settings and higher south-side WWR in cold settings—aligns with established solar-control principles. This study contributes by quantifying these effects under a continuous-operation hospital model, reported per gross floor area in kWh/(m²·yr), using a uniform and TS 825-compliant envelope across three Turkish climate zones (Zones 1, 3, and 6).

This pattern is also consistent with earlier studies reporting climate-dependent annual energy savings—typically in the range of 7–10%—associated with combined effects of orientation, WWR, and glazing properties, comparable to the approximately 6% total-load differences observed in the present study [3]. In hospital ward simulations under arid conditions, orientation and glazing parameters—particularly WWR and U-value—had a measurable impact on cooling demand, with north orientation generally reducing energy use [14]. Similarly, numerical studies in Turkish cities have shown that increased glazing area elevates cooling loads, but that double glazing can substantially mitigate this impact in both summer and winter, especially in cold-dominated locations like Kars [17].

Related simulation-based research in the Turkish context similarly found that increasing WWR on south facades tends to reduce heating loads but can elevate cooling demand, while larger north-facing WWRs generally increase total loads due to higher transmission losses. These findings reinforce this study’s climate-sensitive interpretation of facade performance, particularly the role of solar gains in cold and hot–humid conditions [18].

Daylighting-based evaluations in intensive care settings further support the interpretation that south-facing windows (like S1 in Kars) can deliver daylight and circadian benefits when surface reflectance and window placement are optimized. That work highlighted a WWR of approximately 25% as an effective target for balancing lighting quality and energy use [7].

Beyond thermal and daylight outcomes, some studies have integrated visual comfort and environmental performance through life-cycle assessment (LCA) in healthcare settings. Results reinforced the importance of glazing and orientation decisions for both energy efficiency and occupant well-being—particularly where solar gain coefficients (g-values) strongly influenced cooling loads, even in heating-dominated climates [8].

While the present study was based on a hospital use case, its modeling approach and qualitative insights were also relevant to other large buildings with continuous or near-continuous operation, such as administrative offices, academic facilities, and institutional housing. These building types can exhibit comparable internal gains, HVAC operating schedules, and envelope-related performance constraints. In such contexts, the climate-sensitive WWR–orientation patterns observed in this study—favoring increased north-facing glazing in hot–humid climates and increased south-facing glazing in cold climates—can provide useful design guidance. However, the numerical results reported here should not be directly transferred to non-healthcare buildings without accounting for differences in occupancy profiles, internal loads, ventilation rates, and system operation.

This study focused on annual space-heating and space-cooling loads normalized by gross floor area, as well as on facade-level window heat gains and losses. By quantifying solar gains, transmission losses, and their net balance across orientations, the analysis provided insight into the mechanisms driving whole-building performance. Future research may complement these findings by analyzing peak heating and cooling capacities, daylight autonomy, and visual comfort metrics. Scenario testing of dynamic shading, alternative glazing (e.g., triple glazing for cold climates), and heat-recovery ventilation could further refine envelope strategies—especially under varying occupancy and HVAC schedules. These efforts could be embedded within multi-objective optimization frameworks that balance energy efficiency, thermal comfort, and daylight access in healthcare buildings. This pattern aligns with findings from prior literature on climate-responsive facades. The north–south performance asymmetry observed here—where higher north-side WWRs are preferable in hot–humid settings and higher south-side WWRs in cold settings—is consistent with established solar-control principles. This study contributes by quantifying these effects in a continuous-operation hospital model, using a TS 825-compliant envelope and reporting performance per gross floor area across three Turkish climate zones (Zones 1, 3, and 6).

Overall, orientation-sensitive WWR was shown to be climate-dependent—higher north-facing WWR with low-g glazing and external shading performed best in hot–humid settings, while higher south-facing WWR with lower U-values and moderate-to-high g-values was more effective in cold settings. In temperate regions where energy differences between scenarios were smaller, factors such as daylight access, indoor comfort, and electricity costs may more appropriately guide facade design.